District-level differences in the distribution of mental and substance use disorders in Assam

Vijay Gogoi; Priyadarshee Abhishek; Soumik Sengupta; Indrajeet Banerjee; Samir Sarma; H Sobhana; Sonia P Deuri; Kangkan Pathak; Gautham M Sukumar; Vivek Benegal; Girish N Rao; Mathew Varghese; Gopalkrishna Gururaj

doi:10.4103/indianjpsychiatry.indianjpsychiatry_844_23

District-level differences in the distribution of mental and substance use disorders in Assam

Indian J Psychiatry. 2023 Dec;65(12):1282-1288. doi: 10.4103/indianjpsychiatry.indianjpsychiatry_844_23. Epub 2023 Dec 11.

Authors

Affiliations

¹ Department of Psychiatry, LGBRIMH, Tezpur, Assam, India.
² Department of Clinical Psychology, LGBRIMH, Tezpur, Assam, India.
³ Department of Psychiatric Social Work, LGBRIMH, Tezpur, Assam, India.
⁴ Department of Psychiatry, Kanaklata Civil Hospital, Tezpur, Assam, India.
⁵ Department of Epidemiology, NIMHANS, Bengaluru, Karnataka, India.
⁶ Department of Psychiatry, NIMHANS, Bengaluru, Karnataka, India.
⁷ Department of Epidemiology, Centre for Public Health, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.
⁸ Department of Epidemiology, Centre for Public Health, WHO Collaborative Centre for Injury Prevention and Safety Promotion, National Institute of Mental Health and Neurosciences, Bengaluru, Karnataka, India.

PMID: 38298868
PMCID: PMC10826872
DOI: 10.4103/indianjpsychiatry.indianjpsychiatry_844_23

Abstract

Background: The lifetime prevalence of mental morbidity in Assam is estimated at 8% (NMHS 2015-16). Understanding the distribution patterns of different types of mental disorders among persons with mental morbidity in different districts would facilitate evidence-driven district mental health programming in Assam. Given the varied socio-geopolitical situation across districts in Assam, significant variations in the distribution of mental disorders are expected.

Aims: To assess interdistrict differentials in common mental disorders (CMDs), severe mental disorders (SMDs), socioeconomic impact, healthcare utilization, and mental disability across three districts sampled in NMHS in Assam.

Materials and methods: This cross-sectional study used stratified random cluster sampling to identify and study eligible adult participants in Dibrugarh, Barpeta, and Cachar districts. Standardized scales and validated questionnaires were used to assess mental morbidity, disability, socioeconomic impact, and healthcare utilization. The distribution of different mental disorders among persons with mental disorders and their interdistrict differentials were tested using the Chi-square test of significance.

Results: Among persons with mental morbidity, the most common disorder was CMDs (79%). The proportional distribution of CMDs among persons with mental morbidity was significantly higher in the Dibrugarh district (79%), whereas the distribution of SMDs was higher in the Cachar district (55%). The distribution of alcohol use disorder was the highest in the Dibrugarh district (71.6%). Significant differences in disability and healthcare utilization were observed between the districts.

Conclusions: NMHS 2015-16 Assam indicates significant differentials in the distribution of CMDs and SMDs, healthcare utilization, and associated disability between the three districts. The differentials necessitate further research to understand socio-ethnocultural, religious, geopolitical, and other factors influencing the distribution. These differences need to be accounted for during the implementation of mental health programs in the state.

Keywords: Assam; NMHS; disability; mental morbidity; quintile.